A Disconnection-Pattern-Based Approach for Mapping Spatial Configurations of Vulnerability in Urban Road Networks

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Authors: Chenhao Fang, Chuanpin Wang, Yishuai Zhang, Ling Tian, Yunyan Li
Cited by: 0
References: 37

Abstract

Urban road networks (URNs) underpin critical urban functions ranging from public service provision to emergency response. However, URN resilience is commonly assessed using aggregate performance metrics or critical-element identification, which offers limited insight into how disruption reshapes spatial accessibility. This limitation is increasingly salient under stock-based urban development, where opportunities for large-scale physical network reconfiguration and segment-level engineering interventions are constrained, and resilience enhancement increasingly depends on facility-based adaptation. To address this gap, drawing on graph theory and percolation theory, this study proposes a disconnection-pattern-based (DPB) analytical approach for mapping spatial configurations of URN vulnerability. Two generic disconnection patterns derived from topological limits of network redundancy are conceptualized: Local Island Disconnection (LID) and Global Structural Fragmentation (GSF). Corresponding quantitative mapping methods are developed and applied to cities with contrasting URN morphologies. Results show that spatial configurations of connectivity vulnerability can be systematically mapped across heterogeneous URNs, yielding spatially explicit information critical to resilience-oriented facility siting. By treating vulnerability as a spatial configuration rather than a single-state metric, the proposed approach extends URN resilience assessment toward facility-planning strategies that adapt to existing road-network risk configurations under stock-based development.

Fields of Study & Subjects

Infrastructure Resilience and Vulnerability Analysis Urban Design and Spatial Analysis Disaster Management and Resilience

Publication details

Journal / source
Land
Volume
15
Issue
3
Pages
420–420
Publication date
4 March 2026
Language
EN